[6] An educator might learn to use these AI systems as tools and generate code,[7] text or rich media or optimize their digital content production.
[8] Or a governmental body might see AI as an ideological project to normalize centralized power and decision making,[9] while public schools and higher education contend with increasing privatization.
[15] Resistors often take a principled response and refuse to accept the many metaphors of "artificial intelligence", used to disguise working practices that are exploitative and extractive.
[20] While in the global south, others see the AI's data processing and monitoring as a misguided attempt to address colonialism and inequality, that that has inadvertently re-enforced a neo-liberal approach to education.
AI offers scholars and students automatic assessment and feedback, predictions, instant machine translations, on-demand proof-reading and copy editing, intelligent tutoring or virtual assistants.
Some educationalists have suggested that AI might automate procedural knowledge and expertise[26] or even match or surpass human capacities on cognitive tasks.
[28] Others are more skeptical as AI faces an ethical challenge,[29] where "fabricated responses" or "inaccurate information", politely referred to as "hallucinations"[26] are generated and presented as fact.
Some remain curious about societies tendency to put their faith in engineering achievements, and the systems of power and privilege[30] that leads towards deterministic thinking.
[38] The LLM examines the relationships between tokens, generates probable outputs in response to a prompt, and completes a defined task, such as translating, editing, or writing.
However, the text corpora that LLMs draw on can be problematic, as outputs will reflect their stereotypes or biases of the people or culture whose content has been digitized.
[47] The benefits of multilingualism, grammatically correct sentences or statistically probable texts written about any topic or domain are clear to those who can afford software as a service (SaaS).
New technologies generate a socio technical imaginary (STI) that offer's society, a shared narrative[50] and a collective vision for the future.
[17] AI champions envision a future where machine learning and artificial intelligence might be applied in writing, personalization, feedback or course development.
[56] Post digital scholars and sociologists are more cautious about any techno-solutions, and have warned about the dangers of building public systems around alchemy,[56] stochastic parrots or cognitive capitalism.
Graduates from the majority world also need to value their own process of knowledge construction, resist the lure of normalisation and see AI for what it is, another form of enclosure, and start blogging.
[opinion] Graduates from both the global north and the majority of the world need to be able to critique AI output, become familiar with the processes of technical change,[65] and let their own studies and intellectual life guide their working futures.